Evidence map›Paper›PMID 38690599›Full record

ArticleACS chemical neuroscience2024

Ligand Profiling as a Diagnostic Tool to Differentiate Patient-Derived α-Synuclein Polymorphs.

Timothy S Chisholm, Ronald Melki, Christopher A Hunter

Abstract read
In one paragraph

Article in ACS chemical neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Timothy S ChisholmYusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.ORCID 0000-0002-8693-3797
Ronald MelkiInstitut François Jacob (MIRCen), CEA, CNRS, University Paris-Saclay, 18 Route du Panorama, 92260 Fontenay-aux-Roses, France.
Christopher A HunterYusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.ORCID 0000-0002-5182-1859

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amyloid fibrils are characteristic of many neurodegenerative diseases, including Alzheimer's and Parkinson's diseases. While different diseases may have fibrils formed of the same protein, the supramolecular morphology of these fibrils is disease-specific. Here, a method is reported to distinguish eight morphologically distinct amyloid fibrils based on differences in ligand binding properties. Eight fibrillar polymorphs of α-synuclein (αSyn) were investigated: five generated de novo using recombinant αSyn and three generated using protein misfolding cyclic amplification (PMCA) of recombinant αSyn seeded with brain homogenates from deceased patients diagnosed with Parkinson's disease (PD), multiple system atrophy (MSA), and dementia with Lewy bodies (DLB). Fluorescence binding assays were carried out for each fibril using a toolkit of six different ligands. The fibril samples were separated into five categories based on a binary classification of whether they bound specific ligands or not. Quantitative binding measurements then allowed every fibrillar polymorph to be uniquely identified, and the PMCA fibrils derived from PD, MSA, and DLB patients could be unambiguously distinguished. This approach constitutes a novel and operationally simple method to differentiate amyloid fibril morphologies and to identify disease states using PMCA fibrils obtained by seeding with patient samples.

Indexed as

alpha-SynucleinAmyloidParkinson DiseaseBrainHumansLewy Body DiseaseLigandsMultiple System Atrophyalpha-SynucleinAmyloidLigandsfluorescence binding assayligand binding siteParkinson’s diseasepolymorphsprotein misfolding cyclic amplificationα-synuclein

Identifiers

PMID38690599
PMCPMC11099917

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.